Literature DB >> 31762330

Management of incidental pulmonary nodules: current strategies and future perspectives.

Tae Jung Kim1, Cho Hee Kim1, Ho Yun Lee1, Myung Jin Chung1, Sun Hye Shin2, Kyung Jong Lee2, Kyung Soo Lee1.   

Abstract

Introduction: Detection and characterization of pulmonary nodules is an important issue, because the process is the first step in the management of lung cancers.Areas covered: Literature review was performed on May 15 2019 by using the PubMed, US National Library of Medicine National Institutes of Health, and the National Center for Biotechnology information. CT features helping identify the druggable mutations and predict the prognosis of malignant nodules were presented. Technical advancements in MRI and PET/CT were introduced for providing functional information about malignant nodules. Advances in various tissue biopsy techniques enabling molecular analysis and histologic diagnosis of indeterminate nodules were also presented. New techniques such as radiomics, deep learning (DL) technology, and artificial intelligence showing promise in differentiating between malignant and benign nodules were summarized. Recently, updated management guidelines for solid and subsolid nodules incidentally detected on CT were described. Risk stratification and prediction models for indeterminate nodules under active investigation were briefly summarized.Expert opinion: Advancement in CT knowledge has led to a better correlation between CT features and genomic alterations or tumor histology. Recent advances like PET/CT, MRI, radiomics, and DL-based approach have shown promising results in the characterization and prognostication of pulmonary nodules.

Entities:  

Keywords:  CT; MRI; PET/CT; Pulmonary nodule(s); artificial intelligence; biopsy; management guidelines; radiomics

Year:  2019        PMID: 31762330     DOI: 10.1080/17476348.2020.1697853

Source DB:  PubMed          Journal:  Expert Rev Respir Med        ISSN: 1747-6348            Impact factor:   3.772


  8 in total

1.  Artificial intelligence: radiologists' expectations and opinions gleaned from a nationwide online survey.

Authors:  Francesca Coppola; Lorenzo Faggioni; Daniele Regge; Andrea Giovagnoni; Rita Golfieri; Corrado Bibbolino; Vittorio Miele; Emanuele Neri; Roberto Grassi
Journal:  Radiol Med       Date:  2020-04-29       Impact factor: 3.469

2.  Developing of risk models for small solid and subsolid pulmonary nodules based on clinical and quantitative radiomics features.

Authors:  Rui Zhang; Huaiqiang Sun; Bojiang Chen; Renjie Xu; Weimin Li
Journal:  J Thorac Dis       Date:  2021-07       Impact factor: 2.895

3.  Development, Validation, and Comparison of Image-Based, Clinical Feature-Based and Fusion Artificial Intelligence Diagnostic Models in Differentiating Benign and Malignant Pulmonary Ground-Glass Nodules.

Authors:  Xiang Wang; Man Gao; Jicai Xie; Yanfang Deng; Wenting Tu; Hua Yang; Shuang Liang; Panlong Xu; Mingzi Zhang; Yang Lu; ChiCheng Fu; Qiong Li; Li Fan; Shiyuan Liu
Journal:  Front Oncol       Date:  2022-06-07       Impact factor: 5.738

4.  Pulmonary Nodule Clinical Trial Data Collection and Intelligent Differential Diagnosis for Medical Internet of Things.

Authors:  Weijia Wu; Lizhong Gu; Yuefeng Zhang; Xianping Huang; Weihe Zhou
Journal:  Contrast Media Mol Imaging       Date:  2022-05-26       Impact factor: 3.009

5.  Predicting Lung Cancer Risk of Incidental Solid and Subsolid Pulmonary Nodules in Different Sizes.

Authors:  Rui Zhang; Panwen Tian; Bojiang Chen; Yongzhao Zhou; Weimin Li
Journal:  Cancer Manag Res       Date:  2020-09-04       Impact factor: 3.989

6.  MRI Image Segmentation Model with Support Vector Machine Algorithm in Diagnosis of Solitary Pulmonary Nodule.

Authors:  Bo Feng; Meihua Zhang; Hanlin Zhu; Lingang Wang; Yanli Zheng
Journal:  Contrast Media Mol Imaging       Date:  2021-07-20       Impact factor: 3.161

7.  Application Value of PET/CT and MRI in the Diagnosis and Treatment of Patients With Synchronous Multiple Pulmonary Ground-Glass Nodules.

Authors:  Shaonan Xie; Shaoteng Li; Huiyan Deng; Yaqing Han; Guangjie Liu; Qingyi Liu
Journal:  Front Oncol       Date:  2022-02-23       Impact factor: 6.244

8.  Computed tomography-guided percutaneous microwave ablation: A novel perspective to treat multiple pulmonary ground-glass opacities.

Authors:  Baodong Liu; Xin Ye
Journal:  Thorac Cancer       Date:  2020-08-03       Impact factor: 3.500

  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.